drporthelp

The goal of drporthelp is to display my skill in building a package and creating functions. It is used in my personal online portfolio to take on some of the duplicate code.

The portfolio can be found here.

The portfolio GitHub can be found here.

Installation

You can install the released version of drporthelp from GitHub

install.packages("https://github.com/DanielRoodzantHU/drporthelp")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("DanielRoodzantHU/drporthelp")

Usage

The functions in this package were designed to assist in specific parts of the portfolio.

The coltrans() function transforms column types in the Relational Databases chapter of the portfolio. In the chapter it is used as follows:

# Load the datasets into R datframes
flu_data <- read.csv('data/data_raw/005_relational_databases/flu_data.csv', skip = 11) %>% as_tibble()
dengue_data <- read.csv("data/data_raw/005_relational_databases/dengue_data.csv", skip = 11) %>% as_tibble()

# Tidy the flu_data and dengue_data datasets
flu_data <- flu_data %>% 
  tidyr::pivot_longer(cols = Argentina:Uruguay,
                      names_to = "country", 
                      values_to = "searches"
                      )
dengue_data <- dengue_data %>% 
  tidyr::pivot_longer(cols = Argentina:Venezuela,
                      names_to = "country", 
                      values_to = "searches"
                      )

# Match the column types of the datasets
flu_data <- coltrans(flu_data)
dengue_data <- coltrans(dengue_data)

The datatrans() function transforms the data in two datasets to make them joinable. It is used in the Relational Databases chapter of the portfolio. In the chapter it is used as follows:

# Make the data tables joinable
flu_data <- datatrans(flu_data)
dengue_data <- datatrans(dengue_data)

# Join the data tables
flu_dengue_data <- full_join(flu_data, 
                             dengue_data, 
                             by = c("country", "year"), 
                             suffix = c("_flu", "_dengue")
                             )
gap_flu_dengue_data <- inner_join(flu_dengue_data, 
                                 gapminder, 
                                 by = c("country", "year")
                                 )

The plot_data() function plots specific data from the portfolio into a scatterplot in the C. elegans Plate Experiment chapter of the portfolio. In the chapter it is used as follows:

# Show example of the wrong graph from unedited .xlsx format by retrieving data
wrong_scatter_FLOW.062 <- read_excel(here::here('inst/c_elegans_plate_exp/CE.LIQ.FLOW.062_Tidydata.xlsx'))

# Plotting data using ggplot through a function in drporthelp
wrong_scatter_FLOW.062 %>% drporthelp::plot_data()

The mean_data() function calculates the mean of the Rawdata in the dataset used in the chapter C. elegans Plate Experiment. In the chapter it is used as follows:

# Calculate the mean of the RawData
mean_data_FLOW.062 <- scatter_FLOW.062 %>% mean_data()

For the full results on the use of the functions, please see the corresponding chapters or the vignettes.